Systems and methods for using artificial intelligence and machine learning with a wearable mask to identify a work setting and to control operation of a tool

Abstract

In one embodiment, a computer-implemented method includes receiving, at a wearable mask, first information pertaining to a work setting, wherein the first information comprises video, audio, haptic feedback, or some combination thereof, determining, using an edge processor communicatively coupled to the wearable mask and based on the first information, one or more first characteristics of the work setting, generating, using the edge processor and based on the one or more first characteristics of the work setting, one or more first control instructions configured to modify one or more first operating parameters of a tool, and transmitting, to the tool, the one or more first control instructions to modify the one or more first operating parameters of the tool.

1 . A computer-implemented method comprising:
 receiving, at a wearable mask, first information pertaining to a work setting, wherein the first information comprises video, audio, haptic feedback, or some combination thereof;   determining, using an edge processor communicatively coupled to the wearable mask and based on the first information, one or more first characteristics of the work setting;   generating, using the edge processor and based on the one or more first characteristics of the work setting, one or more first control instructions configured to modify one or more first operating parameters of a tool; and   transmitting, to the tool, the one or more first control instructions to modify the one or more first operating parameters of the tool.   
     
     
         2 . The computer-implemented method of  claim 1 , further comprising:
 receiving, at the wearable mask, second information pertaining to the work setting;   determining, using the edge processor and based on the second information, one or more second characteristics of the work setting, wherein the one or more second characteristics differ from the one or more first characteristics;   generating, using the edge processor and based on the one or more second characteristics of the work setting, one or more second control instructions configured to modify one or more second operating parameters of the tool; and   transmitting, to the tool, the one or more second control instructions to modify the one or more second operating parameters of the tool.   
     
     
         3 . The computer-implemented method of  claim 1 , wherein the one or more first control instructions are transmitted to the tool in real-time or near real-time. 
     
     
         4 . The computer-implemented method of  claim 1 , wherein the one or more characteristics comprise a type of the tool, a type of material being welded, an environmental condition, a weather condition, a type of weld being performed, or some combination thereof. 
     
     
         5 . The computer-implemented method of  claim 1 , wherein the one or more first operating parameters comprise a current, a voltage, a state of operation, a wire feed speed, a temperature, or some combination thereof. 
     
     
         6 . The computer-implemented method of  claim 1 , wherein the tool comprises a welding gun. 
     
     
         7 . The computer-implemented method of  claim 1 , wherein the edge processor executes an artificial intelligence agent comprising one or more machine learning models trained to (i) determine, using the artificial intelligence agent and based on the first information, the one or more first characteristics of the work setting, and (ii) generate, using the artificial intelligence agent and based on the one or more first characteristics of the work setting, the one or more first control instructions configured to modify the one or more first operating parameters of the tool. 
     
     
         8 . The computer-implemented method of  claim 1 , wherein the wearable mask comprises one or more cameras, one or more microphones, one or more sensors, or some combination thereof. 
     
     
         9 . The computer-implemented method of  claim 1 , further comprising:
 displaying, via a virtual retinal display of the wearable mask, second information pertaining to the one or more control instructions; and   receiving, from an input peripheral of the wearable mask, an acceptance or rejection of the one or more control instructions.   
     
     
         10 . One or more tangible, non-transitory computer-readable media storing instructions that, when executed, cause one or more processing devices to:
 receive, at a wearable mask, first information pertaining to a work setting, wherein the first information comprises video, audio, haptic feedback, or some combination thereof;   determine, using an edge processor communicatively coupled to the wearable mask and based on the first information, one or more first characteristics of the work setting;   generate, using the edge processor and based on the one or more first characteristics of the work setting, one or more first control instructions configured to modify one or more first operating parameters of a tool; and   transmit, to the tool, the one or more first control instructions to modify the one or more first operating parameters of the tool.   
     
     
         11 . The computer-readable media of  claim 10 , wherein the one or more processing devices are to:
 receive, at the wearable mask, second information pertaining to the work setting;   determine, using the edge processor and based on the second information, one or more second characteristics of the work setting, wherein the one or more second characteristics differ from the one or more first characteristics;   generate, using the edge processor and based on the one or more second characteristics of the work setting, one or more second control instructions configured to modify one or more second operating parameters of the tool; and   transmit, to the tool, the one or more second control instructions to modify the one or more second operating parameters of the tool.   
     
     
         12 . The computer-readable media of  claim 10 , wherein the one or more first control instructions are transmitted to the tool in real-time or near real-time. 
     
     
         13 . The computer-readable media of  claim 10 , wherein the one or more characteristics comprise a type of the tool, a type of material being welded, an environmental condition, a weather condition, a type of weld being performed, or some combination thereof. 
     
     
         14 . The computer-readable media of  claim 10 , wherein the one or more first operating parameters comprise a current, a voltage, a state of operation, a wire feed speed, a temperature, or some combination thereof. 
     
     
         15 . The computer-readable media of  claim 10 , wherein the tool comprises a welding gun. 
     
     
         16 . The computer-readable media of  claim 10 , wherein the edge processor executes an artificial intelligence agent comprising one or more machine learning models trained to (i) determine, using the artificial intelligence agent and based on the first information, the one or more first characteristics of the work setting, and (ii) generate, using the artificial intelligence agent and based on the one or more first characteristics of the work setting, the one or more first control instructions configured to modify the one or more first operating parameters of the tool. 
     
     
         17 . The computer-readable media of  claim 10 , wherein the wearable mask comprises one or more cameras, one or more microphones, one or more sensors, or some combination thereof. 
     
     
         18 . The computer-readable media of  claim 10 , wherein the one or more processing devices display, via a virtual retinal display of the wearable mask, second information pertaining to the one or more control instructions. 
     
     
         19 . A system comprising:
 one or more memory devices storing instructions; and   one or more processing devices communicatively coupled to the one or more memory devices, wherein the one or more processing execute the instructions to:
 receive, at a wearable mask, first information pertaining to a work setting, wherein the first information comprises video, audio, haptic feedback, or some combination thereof; 
 determine, using an edge processor communicatively coupled to the wearable mask and the first information, one or more first characteristics of the work setting; 
 generate, using the edge processor and based on the one or more first characteristics of the work setting, one or more first control instructions configured to modify one or more first operating parameters of a tool; and 
 transmit, to the tool, the one or more first control instructions to modify the one or more first operating parameters of the tool. 
   
     
     
         20 . The system of  claim 19 , wherein the one or more processing devices are to:
 receive, at the wearable mask, second information pertaining to the work setting;   determine, using the edge processor and based on the second information, one or more second characteristics of the work setting, wherein the one or more second characteristics differ from the one or more first characteristics;   generate, using the edge processor and based on the one or more second characteristics of the work setting, one or more second control instructions configured to modify one or more second operating parameters of the tool; and   transmit, to the tool, the one or more second control instructions to modify the one or more second operating parameters of the tool.